Projects per year
Abstract / Description of output
Mobile Cloud Computing or Fog computing refers to offloading computationally intensive algorithms from a mobile device to the cloud or an intermediate cloud in order to save resources e.g., time and energy in the mobile device. This paper proposes new solutions for situations when the cloud or fog is not available. First, the sensor network is modelled using a network of queues, then a linear programming technique is used to make scheduling decisions. Various centralized and distributed algorithms are then proposed, which improves overall system performance. Extensive simulations show slightly higher energy usage in comparison to the baseline non-offloading case, however, the job completion rate is significantly improved, the efficiency score metric shows the extra energy usage is justified. The algorithms have been simulated in various environments including high and low bandwidth, partial connectivity, and different rate of information exchanges to study the pros and cons of the proposed algorithms.
Original language | English |
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Pages (from-to) | 1499 - 1512 |
Number of pages | 14 |
Journal | IEEE Transactions on Mobile Computing |
Volume | 18 |
Issue number | 7 |
Early online date | 9 Aug 2018 |
DOIs | |
Publication status | Published - 1 Jul 2019 |
Keywords / Materials (for Non-textual outputs)
- Offloading
- Mobile Cloud Computing
- IOT
- Fog Computing
- Edge Computing
Fingerprint
Dive into the research topics of 'Computational Load Balancing on the Edge in Absence of Cloud and Fog'. Together they form a unique fingerprint.Projects
- 1 Finished
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Signal Processing in the Networked Battlespace
Mulgrew, B., Davies, M., Hopgood, J. & Thompson, J.
1/04/13 → 30/06/18
Project: Research
Research output
- 3 Conference contribution
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Distributed Computational Load Balancing for Real-Time Applications
Sthapit, S., Hopgood, J. & Thompson, J., 31 Oct 2017, 25th European Signal Processing Contribution (EUSIPCO 2017).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Offloading to Neighbouring Nodes in Smart Camera Network
Sthapit, S., Hopgood, J., Robertson, N. & Thompson, J., 1 Sept 2016, European Signal Processing Conference (EUSIPCO).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Distributed Implementation for Person Re-identification
Sthapit, S., Thompson, J., Hopgood, J. & Robertson, N., Sept 2015, Sensor Signal Processing for Defence 2015.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Datasets
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Network of Nodes Simulator
Sthapit, S. (Creator), Edinburgh DataShare, 30 Jul 2018
DOI: 10.7488/ds/2397, https://doi.org/10.1109/TMC.2018.2863301
Dataset
Profiles
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James Hopgood
- School of Engineering - Personal Chair of Statistical Signal Processing
- Acoustics and Audio Group
Person: Academic: Research Active